Yangyu Tao

Orcid: 0000-0001-7500-5250

According to our database1, Yangyu Tao authored at least 26 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
OUTRE: An OUT-of-core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine.
Proc. VLDB Endow., July, 2024

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs.
CoRR, 2024

BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics.
CoRR, 2024

Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling.
CoRR, 2024

Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.
CoRR, 2024

NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention.
Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
P<sup>2</sup>CG: a privacy preserving collaborative graph neural network training framework.
VLDB J., July, 2023

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent.
Proc. VLDB Endow., 2023

VEND: Vertex Encoding for Edge Nonexistence Determination.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Graph-Enforced Neural Network for Attributed Graph Clustering.
Proceedings of the Web and Big Data - 7th International Joint Conference, 2023

2022
PaSca: A Graph Neural Architecture Search System under the Scalable Paradigm.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

BlindFL: Vertical Federated Machine Learning without Peeking into Your Data.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

K-core decomposition on super large graphs with limited resources.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Graph Attention Multi-Layer Perceptron.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.
Proc. VLDB Endow., 2021

Graph Attention Multi-Layer Perceptron.
CoRR, 2021

GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing.
CoRR, 2021

VF<sup>2</sup>Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Node Dependent Local Smoothing for Scalable Graph Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Swift: Reliable and Low-Latency Data Processing at Cloud Scale.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2014
Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale.
Proc. VLDB Endow., 2014

2009
Classification via Minimum Incremental Coding Length.
SIAM J. Imaging Sci., 2009

Robust satellite image analysis using probabilistic learning based graph optimization.
Proceedings of the 10th Workshop on Image Analysis for Multimedia Interactive Services, 2009

Learning probabilistic structure to group image edges for object extraction.
Proceedings of the 2009 IEEE International Conference on Multimedia and Expo, 2009

2007
Classification via Minimum Incremental Coding Length (MICL).
Proceedings of the Advances in Neural Information Processing Systems 20, 2007


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